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Publication:2714960
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zbMath1057.62518MaRDI QIDQ2714960

Deborah Nolan, Charles Heilig

Publication date: 2001


Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

U-statisticEmpirical processfunctional central limit theoryuniform weak law of large numbers.


Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Functional limit theorems; invariance principles (60F17) Nonparametric inference (62G99)


Related Items (8)

Estimating invariant laws of linear processes by \(U\)-statistics. ⋮ On extremal distributions and sharp \(L_p\)-bounds for sums of multilinear forms ⋮ Scaling by subsampling for big data, with applications to statistical learning ⋮ On the variable bandwidth kernel estimation of conditional \(U\)-statistics at optimal rates in sup-norm ⋮ Renewal type bootstrap for increasing degree \(U\)-process of a Markov chain ⋮ Weak-convergence of empirical conditional processes and conditional \(U\)-processes involving functional mixing data ⋮ Approximating high-dimensional infinite-order \(U\)-statistics: statistical and computational guarantees ⋮ Central limit theorems for conditional empirical and conditional \(U\)-processes of stationary mixing sequences




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